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Lane-by-Lane Analysis of Crash Occurrence Based on Driver's Lane-Changing and Car-Following Behavior

机译:基于驾驶员的行车道和跟车行为的车道分析

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This study investigates the effects of the traffic flow parameters related to individual drivers' lane-changing and car-following behavior on the occurrence of sideswipe and rear-end crashes on freeways. A total of 184 sideswipe and 605 rear-end crashes on 1-4 freeway in Orlando, Florida, with the loop detector data were used for the analysis. A set of the Bayesian logistic regression models were developed to estimate the likelihood of crashes in a specific lane compared to the adjacent lanes using the 5 min average and lane-by-lane traffic flow parameters. The analysis results showed that the significant traffic flow parameters affecting crash occurrence in a specific lane are distinctively different between sideswipe and rear-end crashes. The flow-related variables were significant in the sideswipe crash models whereas the speed-related variables were significant in the rear-end crash models. The results suggest that the lane-by-lane traffic flow parameters are considered as surrogate measures of lane-changing and car-following behavior that are associated with the occurrence of sideswipe and rear-end crashes. These parameters can potentially be used for real-time monitoring of the likelihood of crash occurrence by lane on instrumented freeways.
机译:这项研究调查了与单个驾驶员的变道和跟车行为有关的交通流参数对高速公路上侧滑和追尾事故的发生的影响。在佛罗里达州奥兰多市的1-4号高速公路上,总共有184次侧向擦拭和605次追尾事故,并使用环路检测器数据进行了分析。开发了一组贝叶斯逻辑回归模型,以使用5分钟平均和逐车道交通流量参数来估计特定车道与相邻车道相撞的可能性。分析结果表明,影响特定车道事故发生的重要交通参数在侧向擦伤和追尾事故之间明显不同。与流量有关的变量在侧擦碰撞模型中很重要,而与速度有关的变量在后端碰撞模型中很重要。结果表明,逐车道交通流参数被认为是与侧向擦拭和追尾事故相关的变道和跟车行为的替代量度。这些参数可以潜在地用于实时监测高速公路上车道发生撞车的可能性。

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